Abstract—Fuzzy logic has a boon for nonlinear control systems. Normal fuzzy logic control with a proportional integral – Derivative (PID) controller is common. Control systems can be defined through transfer functions and statespace. relations for linear systems. Optimal control to meet a performance index is possible only through State Space analysis. Optimal control in state space is centered around the Riccati Equation with state variable functions that has to be solved to yield the control law or trajectory. In the control scheme of an ozone generator, optimal control with a performance index had to be implemented. The method for finding the control functions by solving the equation graphically is described. The data is used for realizing an embedded control scheme for the generator.
Index Terms—Fuzzy control, Neuro- fuzzy Systems, Fuzzy system model, Process control.
G. Venkata Ramu is with the University of Madras, AC College of Technology Campus, Chennai-25, India for pursuing his Ph.D. degree. (email:firstname.lastname@example.org).
K. Padmanabhan is working as Emeritus Professor, AC College of Technology, India. (email: ck_padmanabhan @rediffmail.com)
S. Ananthi is with the Instrumentation Department, University of Madras, AC Tech Campus, Chennai-25, India. (Phone::91-44-22202767; Fax: 91-44-22352494; email: email@example.com).
Cite: G. Venkata Ramu, K. Padmanabhan, and S. Ananthi, "Optimal Control with Fuzzy State Space Modeling Using the Riccati Equation," International Journal of Modeling and Optimization vol. 1, no. 2, pp. 89-94, 2011.